Now liveThe Skillselion MCP - thousands of ranked skills, loaded into your agent mid-task. No install.Get it →
aaron-he-zhu avatar

Keyword Research

  • 6.8k installs
  • 115 repo stars
  • Updated July 13, 2026
  • aaron-he-zhu/seo-geo-claude-skills

A skill that performs systematic keyword research by discovering seed terms, expanding variations with modifiers, classifying search intent, scoring opportunity using volume and difficulty, clustering into topic hubs, an

About

A structured keyword research skill that discovers, scores, and clusters keywords for SEO and GEO planning through an eight-phase workflow. Developers use it when starting keyword research for new pages, topics, or campaigns, or when users ask about search volume, keyword difficulty, topic clusters, or content planning. The skill reads topic/seed keywords and target market data, then outputs a prioritized keyword brief with volume, difficulty, and intent classifications. It groups keywords into pillar and cluster topic hubs, computes opportunity scores using the formula (Volume × Intent Value) / Difficulty, and flags AI-answer-friendly queries. Results include executive summaries, quick wins, growth opportunities, topic clusters, and content calendars saved to memory/research/ directories. The skill integrates optionally with SEO tools or uses a zero-dependency Python helper that harvests keyword ideas from Google Autocomplete.

  • Eight-phase workflow: scope, discover, variations, classify, score, GEO-check, cluster, and deliver actionable keyword b
  • Opportunity scoring formula: (Volume × Intent Value) / Difficulty with intent values 1-3 for informational through trans
  • Zero-dependency local helper using Python script to harvest keyword ideas from Google Autocomplete without paid tools
  • Classifies keywords by intent (informational, navigational, commercial, transactional) and flags GEO-friendly queries li
  • Outputs topic clusters with pillar and hub structure, promotes priorities to memory/hot-cache.md, and chains to competit

Keyword Research by the numbers

  • 6,770 all-time installs (skills.sh)
  • +2 installs in the week ending Jul 28, 2026 (Skillselion tracking)
  • Ranked #106 of 1,881 Marketing & SEO skills by installs in the Skillselion catalog
  • Security screen: MEDIUM risk (skills.sh audit)
  • Data as of Jul 28, 2026 (Skillselion catalog sync)
At a glance

keyword-research capabilities & compatibility

Free for local Python script; optional paid SEO tool integrations for measured volume/difficulty data

Capabilities
keyword discovery · search volume analysis · keyword difficulty scoring · search intent classification · opportunity scoring · topic clustering · geo query detection · content calendar generation
Use cases
seo · research · marketing
Platforms
macOS · Linux · Windows
Runs
Runs locally
Pricing
Free
From the docs

What keyword-research says it does

Example outcome: 150+ keywords analyzed, 23 high-priority opportunities, ~45K/month traffic potential across 3 focus areas.
SKILL.md
npx skills add https://github.com/aaron-he-zhu/seo-geo-claude-skills --skill keyword-research

Add your badge

Show developers this skill is listed on Skillselion. Paste this into your README.

Listed on Skillselion
Installs6.8k
repo stars115
Security audit2 / 3 scanners passed
Last updatedJuly 13, 2026
Repositoryaaron-he-zhu/seo-geo-claude-skills

What it does

Research and prioritize keywords for SEO content planning by analyzing search volume, difficulty, intent, and topic clusters.

Who is it for?

Starting keyword research for new pages, topics, or campaigns; discovering long-tail opportunities; identifying content gaps; planning editorial calendars; and prioritizing keywords by opportunity score when you have bus

Skip if: Competitor-relative coverage gap analysis (use content-gap-analysis instead); rank tracking; backlink research; technical SEO audits; or real-time SERP position monitoring.

When should I use this skill?

User asks to find keywords, 挖词, what to write about, search volume analysis, keyword difficulty, topic clusters, long-tail keywords, 关键词研究, 内容选题, or requests Ahrefs/Google Keyword Planner alternatives.

What you get

A prioritized keyword brief with volume, difficulty, intent, and opportunity scores for each keyword, organized into pillar and cluster topic hubs, with at least three quick win or growth opportunities identified and sav

  • keyword lists
  • topic cluster maps
  • intent classifications

By the numbers

  • Eight-phase workflow covering scope through delivery
  • Intent Value scale 1-3 for informational through transactional keywords
  • Example outcome: 150+ keywords analyzed, 23 high-priority opportunities, ~45K/month traffic potential across 3 focus are

Files

SKILL.mdMarkdownGitHub ↗

Keyword Research

Discovers, scores, and clusters keywords for SEO and GEO planning.

Quick Start

Research keywords for [topic/product/service]
What keywords is [competitor URL] ranking for that I should target?

Skill Contract

Expected output: a prioritized keyword brief plus the standard handoff summary for memory/research/.

  • Reads: topic or seed keyword, target market/language, business goal, site DR, and any user-provided or tool metrics.
  • Writes: a user-facing research deliverable and reusable summary.
  • Promotes: durable keyword priorities, competitor facts, and pending strategy decisions to memory/hot-cache.md, memory/open-loops.md, and memory/research/.
  • Done when: every shortlisted keyword carries volume + difficulty + intent (or a labeled N/A); keywords are grouped into pillar + cluster hubs; and the deliverable names at least 3 prioritized Quick Win / Growth / GEO opportunities.
  • Primary next skill: competitor-analysis when the keyword set is ready for market comparison.

Handoff Summary

Emit the standard shape from skill-contract.md §Handoff Summary Format.

Data Sources

Optional integrations: ~~SEO tool, ~~search console. Without tools, ask for seed keywords, audience, goals, and any known metrics. See CONNECTORS.md.

Zero-dependency local helper (no tool needed): python3 scripts/connectors/suggest.py "<seed>" --expand harvests free keyword ideas from Google Autocomplete (⚠️ unofficial endpoint). Search volume / difficulty still needs ~~SEO tool or own Search Console data. See scripts/connectors/README.md.

Instructions

When a user requests keyword research, run eight phases and announce each as [Phase X/8: Name]:

1. Scope — clarify product, audience, business goal, DR, geography, and language. 2. Discover — seed from core, problem, solution, audience, and industry terms. 3. Variations — expand with modifiers and long-tail patterns. 4. Classify — tag by intent (informational, navigational, commercial, transactional). 5. Score — assign difficulty (1-100) and compute Opportunity = (Volume × Intent Value) / Difficulty, with Intent Value 1 / 1 / 2 / 3. 6. GEO-Check — flag AI-answer-friendly queries such as questions, definitions, comparisons, lists, and how-tos. 7. Cluster — group keywords into pillar + cluster topic hubs. 8. Deliver — output an Executive Summary, Quick Wins / Growth / GEO opportunities, Topic Clusters, Content Calendar, and Next Steps.

Label every metric Measured (tool/export), User-provided, or Estimated (model inference); never present an estimate as measured; if a required metric is unavailable, mark it N/A — do not invent it.

Quality bar: every recommendation includes at least one specific number. Rewrite generic advice into a concrete keyword + volume + difficulty + reason.

Reference: See references/instructions-detail.md for the full 8-phase templates, expansion patterns, intent table, difficulty tiers, opportunity matrix, GEO indicators, cluster template, actionable-vs-generic examples, and advanced usage.

Example

Example outcome: 150+ keywords analyzed, 23 high-priority opportunities, ~45K/month traffic potential across 3 focus areas. See the full sample in references/example-report.md.

Advanced Usage

Intent mapping, seasonal analysis, competitor gaps, and local keyword workflows live in references/instructions-detail.md.

Tips for Success

Start with seeds, respect intent, cluster tightly, prioritize quick wins, and review quarterly. Full notes live in references/instructions-detail.md.

Save Results

Write path: memory/research/keyword-research/YYYY-MM-DD-<topic>.md; promote durable keyword priorities to memory/hot-cache.md. See Skill Contract §Save Results Template.

Reference Materials

Next Best Skill

Primary: competitor-analysis. Also: content-gap-analysis and serp-analysis.

Related skills

How it compares

Pick keyword-research for seed-to-cluster keyword discovery with intent scoring; use an on-page SEO skill when metadata, headings, and schema markup need optimization on existing pages.

FAQ

How does the skill score keyword opportunity without paid SEO tools?

The skill uses the formula (Volume × Intent Value) / Difficulty where Intent Value ranges 1-3. Without tools, it marks metrics as Estimated via model inference or N/A, and offers a zero-dependency Python helper (scripts/connectors/suggest.py) that harvests keyword ideas from Goog

What is the eight-phase workflow and when is research considered done?

The eight phases are: Scope, Discover, Variations, Classify (intent), Score (opportunity), GEO-Check (AI-answer flags), Cluster (pillar/hub), and Deliver (executive summary and next steps). Research is done when every shortlisted keyword has volume + difficulty + intent (or label

How does the skill distinguish between different search intents?

The skill classifies keywords into four intent types: informational (Intent Value 1), navigational (1), commercial (2), and transactional (3), and uses these values in the opportunity score formula. It also flags GEO-friendly queries like questions, definitions, comparisons, list

Is Keyword Research safe to install?

skills.sh reports 2 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.

Marketing & SEOseocontent

This week in AI coding

Five minutes, every Monday - the tools, releases and tactics for developers.

unsubscribe anytime.